{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\research\works\주제40_집_이민자_외국인지원\data\code_robustness_2.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 3 May 2025, 22:02:52

{com}. tsset id year
{res}{txt}{col 8}panel variable:  {res}id (unbalanced)
{txt}{col 9}time variable:  {res}{col 25}year, 2005 to 2022, but with gaps
{txt}{col 17}delta:  {res}1 unit

{com}. xtologit foreigner_right i.immigration##i.homeownership ln_income education sex age marriage capital religion ideology
{res}{txt}
Fitting comparison model:

Iteration 0:{space 3}log likelihood = {res:-5258.0177}  
Iteration 1:{space 3}log likelihood = {res:-5177.1628}  
Iteration 2:{space 3}log likelihood = {res:-5141.9983}  (backed up)
Iteration 3:{space 3}log likelihood = {res:-5137.8433}  
Iteration 4:{space 3}log likelihood = {res:-5137.4807}  
Iteration 5:{space 3}log likelihood = {res:-5137.4803}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-5189.6191}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-5189.6191}  
Iteration 1:{space 3}log likelihood = {res:-5166.4512}  
Iteration 2:{space 3}log likelihood = {res:-5129.4487}  
Iteration 3:{space 3}log likelihood = {res:-5129.3003}  
Iteration 4:{space 3}log likelihood = {res:-5129.3002}  
{res}
{txt}Random-effects ordered logistic regression{col 49}Number of obs{col 67}={col 69}{res}     4,446
{txt}Group variable: {res}id{col 49}{txt}Number of groups{col 67}={col 69}{res}     3,048

{txt}Random effects u_i ~ {res}Gaussian{txt}{col 49}Obs per group:
{col 63}min{col 67}={col 69}{res}         1
{txt}{col 63}avg{col 67}={col 69}{res}       1.5
{txt}{col 63}max{col 67}={col 69}{res}         2

{txt}Integration method: {res}mvaghermite{txt}{col 49}Integration pts.{col 67}={col 70}{res}       12

{txt}{col 49}Wald chi2({res}11{txt}){col 67}={col 70}{res}   196.79
{txt}Log likelihood  = {res}-5129.3002{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000

{txt}{hline 26}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          foreigner_right{col 27}{c |}      Coef.{col 39}   Std. Err.{col 51}      z{col 59}   P>|z|{col 67}     [95% Con{col 80}f. Interval]
{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 25} {c |}
{space 12}1.immigration {c |}{col 27}{res}{space 2} 5.271584{col 39}{space 2} .6372221{col 50}{space 1}    8.27{col 59}{space 3}0.000{col 67}{space 4} 4.022652{col 80}{space 3} 6.520516
{txt}{space 10}1.homeownership {c |}{col 27}{res}{space 2}-.2683471{col 39}{space 2} .0713441{col 50}{space 1}   -3.76{col 59}{space 3}0.000{col 67}{space 4} -.408179{col 80}{space 3}-.1285153
{txt}{space 25} {c |}
immigration#homeownership {c |}
{space 21}1 1  {c |}{col 27}{res}{space 2}-7.471354{col 39}{space 2} .8308394{col 50}{space 1}   -8.99{col 59}{space 3}0.000{col 67}{space 4} -9.09977{col 80}{space 3}-5.842939
{txt}{space 25} {c |}
{space 16}ln_income {c |}{col 27}{res}{space 2}-.1525547{col 39}{space 2} .0587625{col 50}{space 1}   -2.60{col 59}{space 3}0.009{col 67}{space 4} -.267727{col 80}{space 3}-.0373824
{txt}{space 16}education {c |}{col 27}{res}{space 2} .1435015{col 39}{space 2} .0398558{col 50}{space 1}    3.60{col 59}{space 3}0.000{col 67}{space 4} .0653856{col 80}{space 3} .2216175
{txt}{space 22}sex {c |}{col 27}{res}{space 2}-.1161213{col 39}{space 2} .0675809{col 50}{space 1}   -1.72{col 59}{space 3}0.086{col 67}{space 4}-.2485775{col 80}{space 3} .0163348
{txt}{space 22}age {c |}{col 27}{res}{space 2}-.0995509{col 39}{space 2} .0315169{col 50}{space 1}   -3.16{col 59}{space 3}0.002{col 67}{space 4} -.161323{col 80}{space 3}-.0377789
{txt}{space 17}marriage {c |}{col 27}{res}{space 2} .2034719{col 39}{space 2}  .080213{col 50}{space 1}    2.54{col 59}{space 3}0.011{col 67}{space 4} .0462574{col 80}{space 3} .3606865
{txt}{space 18}capital {c |}{col 27}{res}{space 2} .2915686{col 39}{space 2} .0667132{col 50}{space 1}    4.37{col 59}{space 3}0.000{col 67}{space 4} .1608131{col 80}{space 3} .4223241
{txt}{space 17}religion {c |}{col 27}{res}{space 2}-.0561762{col 39}{space 2} .0648691{col 50}{space 1}   -0.87{col 59}{space 3}0.386{col 67}{space 4}-.1833173{col 80}{space 3}  .070965
{txt}{space 17}ideology {c |}{col 27}{res}{space 2}-.0344008{col 39}{space 2}  .035228{col 50}{space 1}   -0.98{col 59}{space 3}0.329{col 67}{space 4}-.1034464{col 80}{space 3} .0346448
{txt}{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 20}/cut1 {c |}{col 27}{res}{space 2}-5.008144{col 39}{space 2} .5511596{col 50}{space 1}   -9.09{col 59}{space 3}0.000{col 67}{space 4}-6.088397{col 80}{space 3}-3.927891
{txt}{space 20}/cut2 {c |}{col 27}{res}{space 2}-2.430039{col 39}{space 2} .5389058{col 50}{space 1}   -4.51{col 59}{space 3}0.000{col 67}{space 4}-3.486275{col 80}{space 3}-1.373803
{txt}{space 20}/cut3 {c |}{col 27}{res}{space 2} .3111494{col 39}{space 2} .5325799{col 50}{space 1}    0.58{col 59}{space 3}0.559{col 67}{space 4}-.7326879{col 80}{space 3} 1.354987
{txt}{space 20}/cut4 {c |}{col 27}{res}{space 2} 2.644824{col 39}{space 2} .5395589{col 50}{space 1}    4.90{col 59}{space 3}0.000{col 67}{space 4} 1.587308{col 80}{space 3}  3.70234
{txt}{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                /sigma2_u {c |}{col 27}{res}{space 2} .4733241{col 39}{space 2} .1342315{col 67}{space 4} .2714962{col 80}{space 3} .8251892
{txt}{hline 26}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}{help j_chibar##|_new:chibar2(01) =}{res} 16.36{col 55}{txt}Prob >= chibar2 = {res}{col 73}0.0000

{com}. 
. estimates store model_1

. 
. 
. 
. xtologit foreigner_right i.immigration##c.ln_house_price ln_income education sex age marriage capital religion ideology
{res}{txt}
Fitting comparison model:

Iteration 0:{space 3}log likelihood = {res: -4940.909}  
Iteration 1:{space 3}log likelihood = {res:-4811.5693}  
Iteration 2:{space 3}log likelihood = {res: -4789.994}  
Iteration 3:{space 3}log likelihood = {res:-4788.5465}  
Iteration 4:{space 3}log likelihood = {res:-4788.5377}  
Iteration 5:{space 3}log likelihood = {res:-4788.5377}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res: -4838.427}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res: -4838.427}  
Iteration 1:{space 3}log likelihood = {res:-4820.6379}  (backed up)
Iteration 2:{space 3}log likelihood = {res:-4785.6271}  
Iteration 3:{space 3}log likelihood = {res:-4781.6198}  
Iteration 4:{space 3}log likelihood = {res:-4781.5572}  
Iteration 5:{space 3}log likelihood = {res:-4781.5572}  
{res}
{txt}Random-effects ordered logistic regression{col 49}Number of obs{col 67}={col 69}{res}     4,183
{txt}Group variable: {res}id{col 49}{txt}Number of groups{col 67}={col 69}{res}     2,900

{txt}Random effects u_i ~ {res}Gaussian{txt}{col 49}Obs per group:
{col 63}min{col 67}={col 69}{res}         1
{txt}{col 63}avg{col 67}={col 69}{res}       1.4
{txt}{col 63}max{col 67}={col 69}{res}         2

{txt}Integration method: {res}mvaghermite{txt}{col 49}Integration pts.{col 67}={col 70}{res}       12

{txt}{col 49}Wald chi2({res}11{txt}){col 67}={col 70}{res}   184.38
{txt}Log likelihood  = {res}-4781.5572{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000

{txt}{hline 29}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             foreigner_right{col 30}{c |}      Coef.{col 42}   Std. Err.{col 54}      z{col 62}   P>|z|{col 70}     [95% Con{col 83}f. Interval]
{hline 29}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 28} {c |}
{space 15}1.immigration {c |}{col 30}{res}{space 2} 50.19395{col 42}{space 2} 7.094342{col 53}{space 1}    7.08{col 62}{space 3}0.000{col 70}{space 4}  36.2893{col 83}{space 3} 64.09861
{txt}{space 14}ln_house_price {c |}{col 30}{res}{space 2}-.1771103{col 42}{space 2} .0262184{col 53}{space 1}   -6.76{col 62}{space 3}0.000{col 70}{space 4}-.2284975{col 83}{space 3}-.1257231
{txt}{space 28} {c |}
immigration#c.ln_house_price {c |}
{space 26}1  {c |}{col 30}{res}{space 2}-5.471557{col 42}{space 2} .7784973{col 53}{space 1}   -7.03{col 62}{space 3}0.000{col 70}{space 4}-6.997383{col 83}{space 3} -3.94573
{txt}{space 28} {c |}
{space 19}ln_income {c |}{col 30}{res}{space 2}-.0607574{col 42}{space 2} .0626376{col 53}{space 1}   -0.97{col 62}{space 3}0.332{col 70}{space 4}-.1835248{col 83}{space 3}   .06201
{txt}{space 19}education {c |}{col 30}{res}{space 2} .2021018{col 42}{space 2} .0418869{col 53}{space 1}    4.82{col 62}{space 3}0.000{col 70}{space 4} .1200049{col 83}{space 3} .2841987
{txt}{space 25}sex {c |}{col 30}{res}{space 2}-.0668682{col 42}{space 2} .0694568{col 53}{space 1}   -0.96{col 62}{space 3}0.336{col 70}{space 4}-.2030011{col 83}{space 3} .0692647
{txt}{space 25}age {c |}{col 30}{res}{space 2}-.0758651{col 42}{space 2} .0326018{col 53}{space 1}   -2.33{col 62}{space 3}0.020{col 70}{space 4}-.1397635{col 83}{space 3}-.0119667
{txt}{space 20}marriage {c |}{col 30}{res}{space 2} .2465928{col 42}{space 2} .0834887{col 53}{space 1}    2.95{col 62}{space 3}0.003{col 70}{space 4} .0829579{col 83}{space 3} .4102277
{txt}{space 21}capital {c |}{col 30}{res}{space 2} .3811498{col 42}{space 2}  .068887{col 53}{space 1}    5.53{col 62}{space 3}0.000{col 70}{space 4} .2461338{col 83}{space 3} .5161658
{txt}{space 20}religion {c |}{col 30}{res}{space 2}-.0392362{col 42}{space 2} .0667331{col 53}{space 1}   -0.59{col 62}{space 3}0.557{col 70}{space 4}-.1700305{col 83}{space 3} .0915582
{txt}{space 20}ideology {c |}{col 30}{res}{space 2}-.0254242{col 42}{space 2} .0362591{col 53}{space 1}   -0.70{col 62}{space 3}0.483{col 70}{space 4}-.0964908{col 83}{space 3} .0456423
{txt}{hline 29}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}/cut1 {c |}{col 30}{res}{space 2}-5.344701{col 42}{space 2} .5742772{col 53}{space 1}   -9.31{col 62}{space 3}0.000{col 70}{space 4}-6.470263{col 83}{space 3}-4.219138
{txt}{space 23}/cut2 {c |}{col 30}{res}{space 2}-2.773997{col 42}{space 2} .5613803{col 53}{space 1}   -4.94{col 62}{space 3}0.000{col 70}{space 4}-3.874282{col 83}{space 3}-1.673712
{txt}{space 23}/cut3 {c |}{col 30}{res}{space 2} -.004156{col 42}{space 2} .5537377{col 53}{space 1}   -0.01{col 62}{space 3}0.994{col 70}{space 4}-1.089462{col 83}{space 3}  1.08115
{txt}{space 23}/cut4 {c |}{col 30}{res}{space 2}  2.35371{col 42}{space 2} .5603664{col 53}{space 1}    4.20{col 62}{space 3}0.000{col 70}{space 4} 1.255412{col 83}{space 3} 3.452008
{txt}{hline 29}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   /sigma2_u {c |}{col 30}{res}{space 2} .4536668{col 42}{space 2} .1384964{col 70}{space 4} .2493907{col 83}{space 3} .8252655
{txt}{hline 29}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}{help j_chibar##|_new:chibar2(01) =}{res} 13.96{col 55}{txt}Prob >= chibar2 = {res}{col 73}0.0001

{com}. 
. estimates store model_2

. 
. 
. 
. xtologit foreigner_support i.immigration##i.homeownership ln_income education sex age marriage capital religion ideology
{res}{txt}
Fitting comparison model:

Iteration 0:{space 3}log likelihood = {res:-5419.3095}  
Iteration 1:{space 3}log likelihood = {res:-5397.2616}  
Iteration 2:{space 3}log likelihood = {res:-5357.5201}  
Iteration 3:{space 3}log likelihood = {res:-5357.3325}  
Iteration 4:{space 3}log likelihood = {res:-5357.3324}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-5403.1151}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-5403.1151}  
Iteration 1:{space 3}log likelihood = {res:-5375.8934}  
Iteration 2:{space 3}log likelihood = {res:-5343.7399}  
Iteration 3:{space 3}log likelihood = {res:-5343.6929}  
Iteration 4:{space 3}log likelihood = {res:-5343.6929}  
{res}
{txt}Random-effects ordered logistic regression{col 49}Number of obs{col 67}={col 69}{res}     4,404
{txt}Group variable: {res}id{col 49}{txt}Number of groups{col 67}={col 69}{res}     3,033

{txt}Random effects u_i ~ {res}Gaussian{txt}{col 49}Obs per group:
{col 63}min{col 67}={col 69}{res}         1
{txt}{col 63}avg{col 67}={col 69}{res}       1.5
{txt}{col 63}max{col 67}={col 69}{res}         2

{txt}Integration method: {res}mvaghermite{txt}{col 49}Integration pts.{col 67}={col 70}{res}       12

{txt}{col 49}Wald chi2({res}11{txt}){col 67}={col 70}{res}   114.73
{txt}Log likelihood  = {res}-5343.6929{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000

{txt}{hline 26}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        foreigner_support{col 27}{c |}      Coef.{col 39}   Std. Err.{col 51}      z{col 59}   P>|z|{col 67}     [95% Con{col 80}f. Interval]
{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 25} {c |}
{space 12}1.immigration {c |}{col 27}{res}{space 2} 3.849589{col 39}{space 2} .5065523{col 50}{space 1}    7.60{col 59}{space 3}0.000{col 67}{space 4} 2.856764{col 80}{space 3} 4.842413
{txt}{space 10}1.homeownership {c |}{col 27}{res}{space 2}-.4345583{col 39}{space 2} .0734557{col 50}{space 1}   -5.92{col 59}{space 3}0.000{col 67}{space 4}-.5785288{col 80}{space 3}-.2905878
{txt}{space 25} {c |}
immigration#homeownership {c |}
{space 21}1 1  {c |}{col 27}{res}{space 2}-3.394117{col 39}{space 2} .7310864{col 50}{space 1}   -4.64{col 59}{space 3}0.000{col 67}{space 4} -4.82702{col 80}{space 3}-1.961215
{txt}{space 25} {c |}
{space 16}ln_income {c |}{col 27}{res}{space 2} .0812237{col 39}{space 2} .0594597{col 50}{space 1}    1.37{col 59}{space 3}0.172{col 67}{space 4}-.0353152{col 80}{space 3} .1977626
{txt}{space 16}education {c |}{col 27}{res}{space 2} .0356647{col 39}{space 2} .0404883{col 50}{space 1}    0.88{col 59}{space 3}0.378{col 67}{space 4} -.043691{col 80}{space 3} .1150203
{txt}{space 22}sex {c |}{col 27}{res}{space 2}-.1256267{col 39}{space 2} .0690955{col 50}{space 1}   -1.82{col 59}{space 3}0.069{col 67}{space 4}-.2610514{col 80}{space 3}  .009798
{txt}{space 22}age {c |}{col 27}{res}{space 2} .0954751{col 39}{space 2} .0318957{col 50}{space 1}    2.99{col 59}{space 3}0.003{col 67}{space 4} .0329607{col 80}{space 3} .1579894
{txt}{space 17}marriage {c |}{col 27}{res}{space 2}-.1020406{col 39}{space 2} .0808942{col 50}{space 1}   -1.26{col 59}{space 3}0.207{col 67}{space 4}-.2605903{col 80}{space 3}  .056509
{txt}{space 18}capital {c |}{col 27}{res}{space 2}-.0242983{col 39}{space 2} .0678437{col 50}{space 1}   -0.36{col 59}{space 3}0.720{col 67}{space 4}-.1572695{col 80}{space 3}  .108673
{txt}{space 17}religion {c |}{col 27}{res}{space 2} .0475018{col 39}{space 2} .0659596{col 50}{space 1}    0.72{col 59}{space 3}0.471{col 67}{space 4}-.0817766{col 80}{space 3} .1767802
{txt}{space 17}ideology {c |}{col 27}{res}{space 2}-.1147281{col 39}{space 2} .0359718{col 50}{space 1}   -3.19{col 59}{space 3}0.001{col 67}{space 4}-.1852314{col 80}{space 3}-.0442247
{txt}{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 20}/cut1 {c |}{col 27}{res}{space 2}-1.982365{col 39}{space 2} .5449775{col 50}{space 1}   -3.64{col 59}{space 3}0.000{col 67}{space 4}-3.050501{col 80}{space 3}-.9142287
{txt}{space 20}/cut2 {c |}{col 27}{res}{space 2}-.2683761{col 39}{space 2} .5416287{col 50}{space 1}   -0.50{col 59}{space 3}0.620{col 67}{space 4}-1.329949{col 80}{space 3} .7931966
{txt}{space 20}/cut3 {c |}{col 27}{res}{space 2} 2.602708{col 39}{space 2} .5440324{col 50}{space 1}    4.78{col 59}{space 3}0.000{col 67}{space 4} 1.536424{col 80}{space 3} 3.668992
{txt}{space 20}/cut4 {c |}{col 27}{res}{space 2} 5.042458{col 39}{space 2} .5596523{col 50}{space 1}    9.01{col 59}{space 3}0.000{col 67}{space 4}  3.94556{col 80}{space 3} 6.139357
{txt}{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                /sigma2_u {c |}{col 27}{res}{space 2} .6042895{col 39}{space 2} .1366261{col 67}{space 4}  .387966{col 80}{space 3} .9412315
{txt}{hline 26}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}{help j_chibar##|_new:chibar2(01) =}{res} 27.28{col 55}{txt}Prob >= chibar2 = {res}{col 73}0.0000

{com}. 
. estimates store model_3

. 
. 
. 
. xtologit foreigner_support i.immigration##c.ln_house_price ln_income education sex age marriage capital religion ideology
{res}{txt}
Fitting comparison model:

Iteration 0:{space 3}log likelihood = {res:-5088.5489}  
Iteration 1:{space 3}log likelihood = {res:-5062.0745}  
Iteration 2:{space 3}log likelihood = {res:-5038.7048}  
Iteration 3:{space 3}log likelihood = {res:-5038.3365}  
Iteration 4:{space 3}log likelihood = {res:-5038.3355}  
Iteration 5:{space 3}log likelihood = {res:-5038.3355}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-5078.8785}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-5078.8785}  
Iteration 1:{space 3}log likelihood = {res:-5056.1017}  
Iteration 2:{space 3}log likelihood = {res: -5023.834}  
Iteration 3:{space 3}log likelihood = {res:-5023.7704}  
Iteration 4:{space 3}log likelihood = {res:-5023.7704}  
{res}
{txt}Random-effects ordered logistic regression{col 49}Number of obs{col 67}={col 69}{res}     4,144
{txt}Group variable: {res}id{col 49}{txt}Number of groups{col 67}={col 69}{res}     2,885

{txt}Random effects u_i ~ {res}Gaussian{txt}{col 49}Obs per group:
{col 63}min{col 67}={col 69}{res}         1
{txt}{col 63}avg{col 67}={col 69}{res}       1.4
{txt}{col 63}max{col 67}={col 69}{res}         2

{txt}Integration method: {res}mvaghermite{txt}{col 49}Integration pts.{col 67}={col 70}{res}       12

{txt}{col 49}Wald chi2({res}11{txt}){col 67}={col 70}{res}    87.09
{txt}Log likelihood  = {res}-5023.7704{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000

{txt}{hline 29}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           foreigner_support{col 30}{c |}      Coef.{col 42}   Std. Err.{col 54}      z{col 62}   P>|z|{col 70}     [95% Con{col 83}f. Interval]
{hline 29}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 28} {c |}
{space 15}1.immigration {c |}{col 30}{res}{space 2} 13.66023{col 42}{space 2} 2.574096{col 53}{space 1}    5.31{col 62}{space 3}0.000{col 70}{space 4} 8.615095{col 83}{space 3} 18.70536
{txt}{space 14}ln_house_price {c |}{col 30}{res}{space 2}-.1374695{col 42}{space 2} .0268637{col 53}{space 1}   -5.12{col 62}{space 3}0.000{col 70}{space 4}-.1901214{col 83}{space 3}-.0848176
{txt}{space 28} {c |}
immigration#c.ln_house_price {c |}
{space 26}1  {c |}{col 30}{res}{space 2}-1.339945{col 42}{space 2} .2890966{col 53}{space 1}   -4.63{col 62}{space 3}0.000{col 70}{space 4}-1.906564{col 83}{space 3}-.7733261
{txt}{space 28} {c |}
{space 19}ln_income {c |}{col 30}{res}{space 2} .1343043{col 42}{space 2}  .064051{col 53}{space 1}    2.10{col 62}{space 3}0.036{col 70}{space 4} .0087666{col 83}{space 3} .2598419
{txt}{space 19}education {c |}{col 30}{res}{space 2} .0706688{col 42}{space 2} .0429372{col 53}{space 1}    1.65{col 62}{space 3}0.100{col 70}{space 4}-.0134866{col 83}{space 3} .1548242
{txt}{space 25}sex {c |}{col 30}{res}{space 2}-.0997158{col 42}{space 2} .0718015{col 53}{space 1}   -1.39{col 62}{space 3}0.165{col 70}{space 4} -.240444{col 83}{space 3} .0410125
{txt}{space 25}age {c |}{col 30}{res}{space 2} .1088131{col 42}{space 2} .0334225{col 53}{space 1}    3.26{col 62}{space 3}0.001{col 70}{space 4} .0433062{col 83}{space 3} .1743199
{txt}{space 20}marriage {c |}{col 30}{res}{space 2}-.1237381{col 42}{space 2} .0850695{col 53}{space 1}   -1.45{col 62}{space 3}0.146{col 70}{space 4}-.2904713{col 83}{space 3} .0429951
{txt}{space 21}capital {c |}{col 30}{res}{space 2} .0458619{col 42}{space 2} .0706422{col 53}{space 1}    0.65{col 62}{space 3}0.516{col 70}{space 4}-.0925943{col 83}{space 3} .1843181
{txt}{space 20}religion {c |}{col 30}{res}{space 2} .0456052{col 42}{space 2} .0684622{col 53}{space 1}    0.67{col 62}{space 3}0.505{col 70}{space 4}-.0885782{col 83}{space 3} .1797886
{txt}{space 20}ideology {c |}{col 30}{res}{space 2}-.1009996{col 42}{space 2} .0372232{col 53}{space 1}   -2.71{col 62}{space 3}0.007{col 70}{space 4}-.1739557{col 83}{space 3}-.0280435
{txt}{hline 29}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}/cut1 {c |}{col 30}{res}{space 2}-2.284755{col 42}{space 2} .5714764{col 53}{space 1}   -4.00{col 62}{space 3}0.000{col 70}{space 4}-3.404828{col 83}{space 3}-1.164682
{txt}{space 23}/cut2 {c |}{col 30}{res}{space 2}-.5856228{col 42}{space 2} .5676938{col 53}{space 1}   -1.03{col 62}{space 3}0.302{col 70}{space 4}-1.698282{col 83}{space 3} .5270365
{txt}{space 23}/cut3 {c |}{col 30}{res}{space 2} 2.325914{col 42}{space 2} .5692847{col 53}{space 1}    4.09{col 62}{space 3}0.000{col 70}{space 4} 1.210136{col 83}{space 3} 3.441691
{txt}{space 23}/cut4 {c |}{col 30}{res}{space 2} 4.780912{col 42}{space 2} .5857816{col 53}{space 1}    8.16{col 62}{space 3}0.000{col 70}{space 4} 3.632801{col 83}{space 3} 5.929023
{txt}{hline 29}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   /sigma2_u {c |}{col 30}{res}{space 2} .6563938{col 42}{space 2} .1454297{col 70}{space 4} .4251806{col 83}{space 3} 1.013341
{txt}{hline 29}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}{help j_chibar##|_new:chibar2(01) =}{res} 29.13{col 55}{txt}Prob >= chibar2 = {res}{col 73}0.0000

{com}. 
. estimates store model_4

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. coefplot (model_1) (model_2), bylabel ((a) DV: Foreigner Right) || (model_3) (model_4), bylabel ((b) DV: Foreigner Support) ||, eform omitted xline(1, lcolor(black) lwidth(thin)) lpattern(dash) graphregion(fcolor(white)) mlabel format(%9.3f) mlabposition(8) mlabsize(tiny) level(95 90) ciopts(lwidth(*0.5 *2))  keep( 1.homeownership || ln_house_price )
{res}
{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\research\works\주제40_집_이민자_외국인지원\data\code_robustness_2.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 3 May 2025, 22:03:37
{txt}{.-}
{smcl}
{txt}{sf}{ul off}